fix back end spelling

README.md

@@ -156,7 +156,7 @@ We welcome contributions! Please review our [contribution guide](CONTRIBUTING.md
 
 This project would not have been possible without the outstanding work from the following communities:
 
-- [Apache Spark](https://spark.apache.org/): Unified Analytics Engine for Big Data, the underlying backend execution engine for .NET for Apache Spark
+- [Apache Spark](https://spark.apache.org/): Unified Analytics Engine for Big Data, the underlying back-end execution engine for .NET for Apache Spark
 - [Mobius](https://github.com/Microsoft/Mobius): C# and F# language binding and extensions to Apache Spark, a pre-cursor project to .NET for Apache Spark from the same Microsoft group.
 - [PySpark](https://spark.apache.org/docs/latest/api/python/index.html): Python bindings for Apache Spark, one of the implementations .NET for Apache Spark derives inspiration from. 
 - [sparkR](https://spark.apache.org/docs/latest/sparkr.html): one of the implementations .NET for Apache Spark derives inspiration from.

deployment/README.md

@@ -35,7 +35,7 @@ Deploying your App on the Cloud
    ```
 
 # Preparing Worker Dependencies
-Microsoft.Spark.Worker is a backend component that lives on the individual worker nodes of your Spark cluster. When you want to execute a C# UDF (user-defined function), Spark needs to understand how to launch the .NET CLR to execute this UDF. Microsoft.Spark.Worker provides a collection of classes to Spark that enable this functionality.
+Microsoft.Spark.Worker is a back-end component that lives on the individual worker nodes of your Spark cluster. When you want to execute a C# UDF (user-defined function), Spark needs to understand how to launch the .NET CLR to execute this UDF. Microsoft.Spark.Worker provides a collection of classes to Spark that enable this functionality.
 
 ## Microsoft.Spark.Worker
 1. Select a [Microsoft.Spark.Worker](https://github.com/dotnet/spark/releases) Linux netcoreapp release to be deployed on your cluster.

docs/developer-guide.md

@@ -16,7 +16,7 @@ spark-submit \
   <path-to-microsoft-spark-jar> \
   debug
 ```
-and you will see the followng output:
+and you will see the following output:
 ```
 ***********************************************************************
 * .NET Backend running debug mode. Press enter to exit *

src/csharp/Microsoft.Spark.E2ETest/SparkFixture.cs

@@ -41,7 +41,7 @@ public class EnvironmentVariableNames
 
         private readonly Process _process = new Process();
         private readonly TemporaryDirectory _tempDirectory = new TemporaryDirectory();
-        
+
         public const string DefaultLogLevel = "ERROR";
 
         internal SparkSession Spark { get; }
@@ -110,7 +110,7 @@ public SparkFixture()
                 .Config("spark.ui.showConsoleProgress", false)
                 .AppName("Microsoft.Spark.E2ETest")
                 .GetOrCreate();
-                
+
             Spark.SparkContext.SetLogLevel(DefaultLogLevel);
 
             Jvm = Spark.Reference.Jvm;

src/csharp/Microsoft.Spark/Services/ConfigurationService.cs

@@ -12,7 +12,7 @@ namespace Microsoft.Spark.Services
 {
     /// <summary>
     /// Implementation of configuration service that helps getting config settings
-    /// to be used in .NET backend.
+    /// to be used in .NET back end.
     /// </summary>
     internal sealed class ConfigurationService : IConfigurationService
     {

src/csharp/Microsoft.Spark/Services/IConfigurationService.cs

@@ -17,7 +17,7 @@ internal interface IConfigurationService
         TimeSpan JvmThreadGCInterval { get; }
 
         /// <summary>
-        /// The port number used for communicating with the .NET backend process.
+        /// The port number used for communicating with the .NET back-end process.
         /// </summary>
         int GetBackendPortNumber();
 

src/scala/microsoft-spark-3-0/src/main/scala/org/apache/spark/deploy/dotnet/DotnetRunner.scala

@@ -112,7 +112,7 @@ object DotnetRunner extends Logging {
     val dotnetBackendThread = new Thread("DotnetBackend") {
       override def run() {
         // need to get back dotnetBackendPortNumber because if the value passed to init is 0
-        // the port number is dynamically assigned in the backend
+        // the port number is dynamically assigned in the back end
         dotnetBackendPortNumber = dotnetBackend.init(dotnetBackendPortNumber)
         logInfo(s"Port number used by DotnetBackend is $dotnetBackendPortNumber")
         initialized.release()

src/scala/microsoft-spark-3-1/src/main/scala/org/apache/spark/deploy/dotnet/DotnetRunner.scala

@@ -112,7 +112,7 @@ object DotnetRunner extends Logging {
     val dotnetBackendThread = new Thread("DotnetBackend") {
       override def run() {
         // need to get back dotnetBackendPortNumber because if the value passed to init is 0
-        // the port number is dynamically assigned in the backend
+        // the port number is dynamically assigned in the back end
         dotnetBackendPortNumber = dotnetBackend.init(dotnetBackendPortNumber)
         logInfo(s"Port number used by DotnetBackend is $dotnetBackendPortNumber")
         initialized.release()